Using RF transmissions from IoT devices for occupancy detection and activity recognition
Using RF transmissions from IoT devices for occupancy detection and activity recognition
IoT ecosystems consist of a range of smart devices that generated a plethora of Radio Frequency (RF) transmissions. This provides an attractive opportunity to exploit already-existing signals for various sensing applications such as e-Healthcare, security and smart home. In this paper, we present Passive IoT Radar (PIoTR), a system that passively uses RF transmissions from IoT devices for human monitoring. PIoTR is designed based on passive radar technology, with a generic architecture to utilize various signal sources including the WiFi signal and wireless energy at the Industrial, Scientific and Medical (ISM) band. PIoTR calculates the phase shifts caused by human motions and generates Doppler spectrogram as the representative. To verify the proposed concepts and test in a more realistic environment, we evaluate PIoTR with four commercial IoT devices for home use. Depending on the effective signal and power strength, PIoTR performs two modes: coarse sensing and fine-grained sensing. Experimental results show that PIoTR can achieve an average of 91% in occupancy detection (coarse sensing) and 91.3% in activity recognition (fine-grained sensing).
Gesture recognition, IoT devices, Occupancy detection, Wireless sensing sensor
2484-2495
Li, Wenda
3a3026d2-6265-4fb9-9b4e-22082087909e
Vishwakarma, Shelly
c98f51e0-a07e-4b21-becd-75d7249643ea
Tang, Chong
9409c6d1-69d2-4598-8b43-bbb7f51f6fe2
Woodbridge, Karl
5234b3c0-6313-4513-8309-28b824a14fb6
Piechocki, Robert J.
7e476884-c4fc-48a7-af9b-62e583cb79ee
Chetty, Kevin
324e29d3-cdf5-4e2b-9b78-5fad57f4e4d0
1 February 2022
Li, Wenda
3a3026d2-6265-4fb9-9b4e-22082087909e
Vishwakarma, Shelly
c98f51e0-a07e-4b21-becd-75d7249643ea
Tang, Chong
9409c6d1-69d2-4598-8b43-bbb7f51f6fe2
Woodbridge, Karl
5234b3c0-6313-4513-8309-28b824a14fb6
Piechocki, Robert J.
7e476884-c4fc-48a7-af9b-62e583cb79ee
Chetty, Kevin
324e29d3-cdf5-4e2b-9b78-5fad57f4e4d0
Li, Wenda, Vishwakarma, Shelly, Tang, Chong, Woodbridge, Karl, Piechocki, Robert J. and Chetty, Kevin
(2022)
Using RF transmissions from IoT devices for occupancy detection and activity recognition.
IEEE Sensors Journal, 22 (3), .
(doi:10.1109/JSEN.2021.3134895).
Abstract
IoT ecosystems consist of a range of smart devices that generated a plethora of Radio Frequency (RF) transmissions. This provides an attractive opportunity to exploit already-existing signals for various sensing applications such as e-Healthcare, security and smart home. In this paper, we present Passive IoT Radar (PIoTR), a system that passively uses RF transmissions from IoT devices for human monitoring. PIoTR is designed based on passive radar technology, with a generic architecture to utilize various signal sources including the WiFi signal and wireless energy at the Industrial, Scientific and Medical (ISM) band. PIoTR calculates the phase shifts caused by human motions and generates Doppler spectrogram as the representative. To verify the proposed concepts and test in a more realistic environment, we evaluate PIoTR with four commercial IoT devices for home use. Depending on the effective signal and power strength, PIoTR performs two modes: coarse sensing and fine-grained sensing. Experimental results show that PIoTR can achieve an average of 91% in occupancy detection (coarse sensing) and 91.3% in activity recognition (fine-grained sensing).
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Published date: 1 February 2022
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Publisher Copyright:
© 2001-2012 IEEE.
Keywords:
Gesture recognition, IoT devices, Occupancy detection, Wireless sensing sensor
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Local EPrints ID: 503399
URI: http://eprints.soton.ac.uk/id/eprint/503399
ISSN: 1530-437X
PURE UUID: 40b23f1d-7564-413f-b261-7fa04ec33320
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Date deposited: 30 Jul 2025 16:52
Last modified: 31 Jul 2025 02:03
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Contributors
Author:
Wenda Li
Author:
Shelly Vishwakarma
Author:
Chong Tang
Author:
Karl Woodbridge
Author:
Robert J. Piechocki
Author:
Kevin Chetty
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